Application of Particle Vector Model in Smart Teaching Management System

Abstract

In the current education model, in order to improve the teaching quality of teachers, the established teaching system can push the teaching data and conclusions to the teachers themselves or the school, which helps to understand the teaching situation in many ways, so as to improve the teaching methods of teachers in the classroom. Develop targeted solutions to the problems that arise. This paper is based on the particle swarm algorithm, combined with particle cluster calculation and feature intensive fusion, to analyze the teacher's behavior in the classroom scene, aiming to improve the accuracy of teacher behavior recognition, make full use of video resources to assist in the analysis of the teacher's overall behavior, thereby automatically generating teaching Ways to evaluate.